library(tidyverse)
library(plotly)
Penguins<-read.csv("penguins_size.csv")
Penguins
dim(Penguins)
[1] 344   7
summary(Penguins)
   species             island          culmen_length_mm culmen_depth_mm flipper_length_mm
 Length:344         Length:344         Min.   :32.10    Min.   :13.10   Min.   :172.0    
 Class :character   Class :character   1st Qu.:39.23    1st Qu.:15.60   1st Qu.:190.0    
 Mode  :character   Mode  :character   Median :44.45    Median :17.30   Median :197.0    
                                       Mean   :43.92    Mean   :17.15   Mean   :200.9    
                                       3rd Qu.:48.50    3rd Qu.:18.70   3rd Qu.:213.0    
                                       Max.   :59.60    Max.   :21.50   Max.   :231.0    
                                       NA's   :2        NA's   :2       NA's   :2        
  body_mass_g       sex           
 Min.   :2700   Length:344        
 1st Qu.:3550   Class :character  
 Median :4050   Mode  :character  
 Mean   :4202                     
 3rd Qu.:4750                     
 Max.   :6300                     
 NA's   :2                        
Penguins$species<-as.factor(Penguins$species)
Penguins$island<-as.factor(Penguins$island)
#Penguins$sex<-as.factor(Penguins$sex)
summary(Penguins)
      species          island    culmen_length_mm culmen_depth_mm flipper_length_mm
 Adelie   :152   Biscoe   :168   Min.   :32.10    Min.   :13.10   Min.   :172.0    
 Chinstrap: 68   Dream    :124   1st Qu.:39.23    1st Qu.:15.60   1st Qu.:190.0    
 Gentoo   :124   Torgersen: 52   Median :44.45    Median :17.30   Median :197.0    
                                 Mean   :43.92    Mean   :17.15   Mean   :200.9    
                                 3rd Qu.:48.50    3rd Qu.:18.70   3rd Qu.:213.0    
                                 Max.   :59.60    Max.   :21.50   Max.   :231.0    
                                 NA's   :2        NA's   :2       NA's   :2        
  body_mass_g       sex           
 Min.   :2700   Length:344        
 1st Qu.:3550   Class :character  
 Median :4050   Mode  :character  
 Mean   :4202                     
 3rd Qu.:4750                     
 Max.   :6300                     
 NA's   :2                        
Clean_DF<-na.omit(Penguins)
Clean_DF<-Clean_DF%>%
  filter(sex == 'FEMALE' | sex == 'MALE')
summary(Clean_DF)
      species          island    culmen_length_mm culmen_depth_mm flipper_length_mm
 Adelie   :146   Biscoe   :163   Min.   :32.10    Min.   :13.10   Min.   :172      
 Chinstrap: 68   Dream    :123   1st Qu.:39.50    1st Qu.:15.60   1st Qu.:190      
 Gentoo   :119   Torgersen: 47   Median :44.50    Median :17.30   Median :197      
                                 Mean   :43.99    Mean   :17.16   Mean   :201      
                                 3rd Qu.:48.60    3rd Qu.:18.70   3rd Qu.:213      
                                 Max.   :59.60    Max.   :21.50   Max.   :231      
  body_mass_g       sex           
 Min.   :2700   Length:333        
 1st Qu.:3550   Class :character  
 Median :4050   Mode  :character  
 Mean   :4207                     
 3rd Qu.:4775                     
 Max.   :6300                     
Clean_DF$sex<-as.factor(Clean_DF$sex)
boxplot(Clean_DF[3:5])

boxplot(Clean_DF$body_mass_g)

p<-ggplot(Clean_DF, aes(sex, body_mass_g, fill=sex))+
  geom_boxplot()

ggplotly(p)
p<-ggplot(Clean_DF, aes(sex, culmen_length_mm, fill=sex))+
  geom_boxplot()

ggplotly(p)
p<-ggplot(Clean_DF, aes(sex, culmen_depth_mm, fill=sex))+
  geom_boxplot()

ggplotly(p)
p<-ggplot(Clean_DF, aes(sex, flipper_length_mm, fill=sex))+
  geom_boxplot()

ggplotly(p)

Looking at body measures by Species

p<-ggplot(Clean_DF, aes(species, body_mass_g, fill=species))+
  geom_boxplot()

ggplotly(p)
p<-ggplot(Clean_DF, aes(species, culmen_length_mm, fill=species))+
  geom_boxplot()

ggplotly(p)
p<-ggplot(Clean_DF, aes(species, culmen_depth_mm, fill=species))+
  geom_boxplot()

ggplotly(p)
p<-ggplot(Clean_DF, aes(species, flipper_length_mm, fill=species))+
  geom_boxplot()

ggplotly(p)
p<-ggplot(Clean_DF,aes(species,island, colour=species))+
  geom_point()+
  geom_jitter()
  

ggplotly(p)
p<-ggplot(data = Clean_DF) + 
  geom_point(mapping = aes(x = culmen_length_mm, y = culmen_depth_mm,color = species, shape=island))

ggplotly(p)
p<-ggplot(data = Clean_DF) + 
  geom_point(mapping = aes(x = culmen_length_mm, y = flipper_length_mm,color = species, shape=island))

ggplotly(p)
p<-ggplot(data = Clean_DF) + 
  geom_point(mapping = aes(x = culmen_length_mm, y = body_mass_g, color = species, shape=island))

ggplotly(p)
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